As the artificial intelligence market is projected to grow by 53% in by 2020, advertisers are looking for ways to use the technology to their advantage. Vernon Vasu, CMO at ReFUEL4 states that researchers are looking into using AI for creative development in the future, but for now advertisers can use AI's incredible data mining and organizing capabilities to understand audiences like never before Artificial intelligence is one of the most buzzed-about terms in technology. The AI market is estimated to reach 5.05 billion USD by 2020, up from 419.7 million USD in 2014 – a 53% increase. With the launch of Facebook's chatbots, Amazon's Echo, and IBM's Watson, companies in many fields are considering how they can use new AI tools to their advantage. Advertising agencies that use AI, machine learning, and image recognition are hyper-targeting consumers by learning their interests and tastes.

Three years ago, Jeff Bezos announced that drones are eventually going to deliver Amazon orders. In the past year, he brought out Amazon's Alexa artificial intelligence service, which understands speech well enough that you can say, "Alexa, I really need a waffle cone maker," and she'll put one in your Amazon online shopping cart, even though nobody needs a waffle cone maker. Both of these technologies--drones and cloud AI--are exciting today, yet still wobbly works in progress. But in coming years, Amazon or some other company is going to put them together. And that, finally, will evolve into a technology that could become as significant to humans as domesticated dogs.

Self-driving vehicles promised to revolutionize the transportation industry. Automated cars could reshape every industry that relies on the automobile, from car manufacturing, to taxis, limousines and trucking. By taking human beings--who aren't the drivers they think they are--out from behind the wheel, self-driving cars could also save millions of lives. Self-driving cars will also have a profound effect on the environment--but whether it's for better or for worse will depend on technological and policy choices that have yet to be made. Automated vehicles could reduce energy consumption in transportation by as much as 90%, or increase it by more than 200%, according to research from the Department of Energy (DOE).

"Don't you know who I am?" Yes, your Uber driver or AirBnB host may see your star rating and past reviews, but how they combine that data with the context of their current experience with you may vary. According to the 2015 Gartner Hype Cycle, machine learning, internet of things, natural language processing and hybrid cloud computing should have all matured past the "peak of inflated expectations" at roughly the same time. The 2016 Gartner Hype Cycle shows this trend continuing (plus drones). This confluence seems to be driving the emergence of cognitive systems, which thrive on context and help businesses recognize customers and solve for their unique needs at scale. Without the aid of machine learning, the process of providing context needed for humans to leverage data in a personalized way does not scale.

Marc Andreessen once said that software was eating the world. The point he was trying to make was that software increasingly represents the value in most economic processes. In this sense, where software was previously one small component of a complex process that involved lots of human input and complex non-digital systems, it now represents the bulk of the intelligence and value-add. Think about cars before Tesla. You had carburetors, fuel injection systems, spark plugs, complex mechanical transmission systems, cooling systems, pumps and much more.

Zenedge just raised 6.2 million in Series C funding, led by Pilot Growth Equity. Additional funds come from Zoho Corporation and existing investors TELUS Ventures and Yehuda Neuberger. Founded in 2014, Zenedge is a leading provider of cloud-based, artificial intelligence, driven Web Application Firewall (WAF) and Distributed Denial of Service (DDoS) cybersecurity Infrastructure-as- a-Service (IaaS) provider. The company leverages patent-pending deep machine-learning capabilities to detect anomalies, dynamically alter security postures, and initiate auto-mitigation and automatic routing with minimal to zero human intervention. This allows the company to provide better cybersecurity and faster time to mitigation than traditional cloud and on-premise cybersecurity vendors, ultimately resulting in less and shorter business interruptions, while helping reduce operational costs.

IPhone owners will get an upgrade on September 13 that allows them to find a picture of nearly anyone or anything, anywhere and from any time. Neural network artificial intelligence in the new iOS 10 performs 11 billion calculations in a tenth of a second on each photo snapped to figure out who people are and even what mood they're in. Aipoly, an app released in January, recognizes objects and speaks their names aloud to blind people. Google Translate can replace text in one language with another language as soon as you point your camera at it. All this happens even if you can't get cell reception.

HENDERSON, Nev.--(BUSINESS WIRE)--Quertle LLC has developed the first artificial intelligence and visual analytics big data (BioAI) platform for biomedical drug discovery. This platform combines machine learning, neural networks, and other AI methods to improve discovery and insight. The BioAI platform includes predictive visual analytics that accelerate search and discovery from the literature, enable discovery of documents that are otherwise overlooked and improve drug discovery. The AI-powered visualizations summarize an entire set of documents, detect trends and uncover hidden connections. Biomedical literature is the foundation of the 5 trillion health care market, serving as the basis for drug discovery, medical device opportunities, marketing decisions and direct health care.

Welcome to robot nursery school," Pieter Abbeel says as he opens the door to the Robot Learning Lab on the seventh floor of a sleek new building on the northern edge of the UC-Berkeley campus. The lab is chaotic: bikes leaning against the wall, a dozen or so grad students in disorganized cubicles, whiteboards covered with indecipherable equations. Abbeel, 38, is a thin, wiry guy, dressed in jeans and a stretched-out T-shirt. He moved to the U.S. from Belgium in 2000 to get a Ph.D. in computer science at Stanford and is now one of the world's foremost experts in understanding the challenge of teaching robots to think intelligently. But first, he has to teach them to "think" at all. "That's why we call this nursery school," he jokes. He introduces me to Brett, a six-foot-tall humanoid robot made by Willow Garage, a high-profile Silicon Valley robotics manufacturer that is now out of business. The lab acquired the robot several years ago to experiment with. Brett, which stands for ...

But research developed in part by NASA's Jet Propulsion Laboratory, Pasadena, California, may change that, introducing artificial intelligence (AI) that could collect data on temperatures, gases and other danger signals and guide a team of first responders safely through the flames. AUDREY, the Assistant for Understanding Data through Reasoning, Extraction, and sYnthesis, has received the Undersecretary's Award for Collaboration from the Department of Homeland Security (DHS) in recognition of its joint development by JPL and DHS. It's part of the Next Generation First Responder (NGFR) program, a DHS initiative to innovate new ways to keep firefighters, police, paramedics and other first responders safe in the field through increased awareness of their surroundings and communication abilities. But the big picture is even more exciting: AUDREY can track an entire team of firefighters, sending relevant signals to individuals while helping to make recommendations for how they could work together. "As a firefighter moves through an environment, AUDREY could send alerts through a mobile device or head-mounted display," said Mark James of JPL, lead scientist for the AUDREY project.